• 한국자동차공학회논문집
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• 제24권4호
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• pp.408-415
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• 2016

The vehicle attitude and sideslip is critical information to control the vehicle to prevent from unintended motion. Many of estimation strategy use bicycle model or IMU integration, but both of them have limits on application. The main purpose of this paper is development of vehicle orientation estimator which is robust to various vehicle state and road shape. The suggested estimator use 3-axis magnetometer, yaw rate sensor and lateral acceleration sensor to estimate three Euler angles of vehicle. The estimator is composed of two individual observers: First, comparing the known magnetic field and gravity with measured value, the TRIAD algorithm calculates optimal rotational matrix when vehicle is in static or quasi-static condition. Next, merging 3-axis magnetometer with inertial sensors, the extended Kalman filter is used to estimate vehicle orientation under dynamic condition. A validation through simulation tools, Carsim and Simulink, is performed and the results show the feasibility of the suggested estimation method.

• 센서학회지
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• 제27권3호
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• pp.165-169
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• 2018

A single-axis Cubli frame realized simply with an IMU sensor and DC motor is presented herein. To maintain the balance on the Cubli frame, an LQR controller based on a Lagrangian derivation of the dynamics was designed, which utilized the state variables of the frame angle and its angular acceleration, as well as the wheel angle and its angular acceleration. The designed LQR controller showed a settling time balancing capability of approximately two seconds and 40% of the maximum overshoot in Matlab/Simulink simulations. Our experimental results of the fabricated Cubli frame matched with the simulation results. It maintained balancing at the reference position even though an initial offset as well as external disturbance during the balancing was applied.

• 로봇학회논문지
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• 제15권1호
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• pp.32-38
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• 2020

This paper describes a method for tracking attitude and position of underwater robots. Underwater work with underwater robots is subject to differences in work efficiency depending on the skill of the operator and the utilization of additional sensors. Therefore, this study developed an underwater robot that can operate autonomously and maintain a certain attitude when working underwater to reduce difference of work efficiency. The developed underwater robot uses 8 thrusters to control 6 degrees of freedom motion, IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and PS (Pressure Sensor) to measure attitude and position. In addition, the thruster allocation algorithm was designed to follow the control desired value using 8 thrusters, and the motion control experiments were performed in the engineering water basin using the thruster allocation method.

• 제어로봇시스템학회논문지
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• 제15권10호
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• pp.1002-1008
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• 2009

We consider a double faults detection and isolation problem using modified extended parity space approach for inertial measurement unit which use redundant inertial sensors. A redundant IMU which has a hardware redundant is composed of the cone shape because it is good for fault detection and isolation. We analyze the type of double faults and the reason why fault isolation performance is low. We propose modified extended parity space approach method using EPSA and the difference of sensor data.

• 제어로봇시스템학회논문지
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• 제19권9호
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• pp.834-838
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• 2013

This paper proposes a new ball robot which has a four axis structure and four motors that directly actuate the ball to move or to maintain the balance of the robot. For the Balancing control, it is possible to use non-model-based controller to control simply without complex formula. All the gains of the controller are heuristically adjusted during the experiments. The tilt angle is measured by IMU sensors, which is used to generate the control input of the roll and pitch controller to make the tilt angle zero. The performance of the designed control system has been verified through the real experiments with the developed ball robot.

• 제어로봇시스템학회논문지
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• 제13권2호
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• pp.101-107
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• 2007

A coaxial rotor flying robot is developed for surveying and reconnoitering various circumstances under calamity environment. The robot has two contrarotating rotors on a common axis, an embedded microcontroller, an IMU(Inertial Measurement Unit), an IR sensor for height control, a micro camera for surveillance, ultrasonic position sensors and wireless communication devices. A bell-bar mounted on the top of the upper rotor hub increases stability and improves flight performance. In this paper, we present a dynamic model of a coaxial rotor flying robot and design an embedded controller far the robot, and implement them to control the developed flying robot. Experimental results show that the proposed controller is valid for autonomous hovering and position control.

• IEIE Transactions on Smart Processing and Computing
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• 제4권4호
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• pp.216-223
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• 2015

The autonomous underwater vehicle (AUV) is being widely researched in order to achieve superior performance when working in hazardous environments. This research focuses on using image processing techniques to estimate the AUV's egomotion and the changes in orientation, based on image frames from different time frames captured from a single high-definition web camera attached to the bottom of the AUV. A visual odometry application is integrated with other sensors. An internal measurement unit (IMU) sensor is used to determine a correct set of answers corresponding to a homography motion equation. A pressure sensor is used to resolve image scale ambiguity. Uncertainty estimation is computed to correct drift that occurs in the system by using a Jacobian method, singular value decomposition, and backward and forward error propagation.

• 전기학회논문지
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• 제68권1호
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• pp.189-198
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• 2019

In recent years, visual-inertial odometry(VIO) algorithms have been extensively studied for the indoor/urban environments because it is more robust to dynamic scenes and environment changes. In this paper, we propose loosely coupled(LC) VIO algorithm that utilizes the velocity vectors from both visual odometry(VO) and inertial measurement unit(IMU) as a filter measurement of Extended Kalman filter. Our approach improves the estimation performance of a filter without adding extra sensors while maintaining simple integration framework, which treats VO as a black box. For the VO algorithm, we employed a fundamental part of the ORB-SLAM, which uses ORB features. We performed an outdoor experiment using an RGB-D camera to evaluate the accuracy of the presented algorithm. Also, we evaluated our algorithm with the public dataset to compare with other visual navigation systems.

• 한국컴퓨터정보학회논문지
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• 제25권1호
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• pp.63-69
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• 2020

본 논문에서는 상대적인 액세스 포인트의 신호 강도에 기초한 랜드마크를 사용하는 실내 위치 추적 기법에 대하여 제안한다. AP 신호의 절댓값은 기존의 실내 위치 추적 기술에 사용되었지만, 측정 기기, 측정 환경, 그리고 측정 시기의 변동으로 인해 달라질 수 있다. 그러나 우리는 특정 장소에서는 AP의 수신 신호 세기의 흐름이 서의 일정한 패턴을 나타낸다는 사실을 알아냈다. 그 특징에 따라, 우리는 AP들 간의 상대적 강도를 파악하고, 그들이 특정 패턴을 보이는 특정 장소를 랜드마크로서 저장한다. 랜드마크 맵 배치가 완료되면, 시스템은 스마트폰의 IMU 센서를 사용하여 사용자의 위치를 계산하고 저장된 랜드마크로 보정한다. 우리의 시스템은 센서만 사용한 기술에 비하여 75.2%의 개선을, 그리고 절댓값으로 선택된 랜드마크를 사용한 기술에 비하여 39.6%의 개선을 보인다.

• 방송공학회논문지
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• 제25권4호
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• pp.528-536
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• 2020

휴머노이드 로봇 기술이 발전함에 따라서 로봇을 공연에 활용하는 사례가 늘어나고 있다. 이에 따라서 로봇의 동작을 사람처럼 자연스럽게 표현하여 공연에서의 활용범위를 보다 높이기 위한 연구들이 진행되고 있다. 이 중 모션캡쳐 기술을 이용하는 방식이 많이 사용되고 있는데, 일반적으로 모션 캡처를 하기 위해서 신체에 각 부위에 부착된 IMU 센서 혹은 마커들과 정밀한 고성능 카메라가 요구되는 등 준비하는 데에서 환경적인 불편함이 존재한다. 또한, 공연기술에 사용되는 로봇의 경우에는 실시간으로 돌발상황이나 관객의 반응에 따라서 실시간으로 대응해야 하는 문제가 존재한다. 본 논문에서는 위에서 언급한 문제들을 보완하고자 다수의 RGB-D 카메라를 이용한 실시간 모션캡쳐 시스템을 구축하고, 모션 캡쳐된 데이터를 이용하여 사람 동작과 유사한 자연스러운 로봇 동작을 생성하는 방법을 제안한다.